Search Results - (( pareto optimization based algorithm ) OR ( parameter optimization path algorithm ))
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…The IEEE RTS 26, 32 and 36-unit dataset systems were used in the performance evaluation of the PACS algorithm. The performance of PACS algorithm was compared against four benchmark multi-objective algorithms including the Nondominated Sorting Genetic, Strength Pareto Evolutionary, Simulated Annealing, and Particle Swarm Optimization using the metrics grey relational grade (GRG), coverage, distance to Pareto front, Pareto spread, and number of non-dominated solutions. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…Simulation results reveal the proposed algorithm’s ability to produce real and well-distributed Pareto optimum fronts for all considered multi-objective optimization cases. …”
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Hybridization of Strength Pareto Multiobjective Optimization with Modified Cuckoo Search Algorithm for Rectangular Array
Published 2017“…In addition, the MCS algorithm is hybridized with the particle swarm optimization (PSO) and hill climbing (HC) stochastic techniques along with the standard strength Pareto evolutionary algorithm (SPEA) forming the MCSPSOSPEA and MCSHCSPEA, respectively.All the proposed MCS-based algorithms are examined to perform MO optimization on Zitzler–Deb–Thiele’s (ZDT’s) test functions. …”
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Multi-objective spiral dynamic algorithms-based for a better accuracy and diversity
Published 2019“…This thesis presents two variants of multi-objective type algorithms based on a Spiral Dynamic Algorithm (SDA) with application to optimize a Proportional-Derivative (PD) controller for an Inverted Pendulum System. …”
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Pareto ensembles for evolutionary synthesis of Neurocontrollers in a 2D maze-based video game
Published 2013“…In this paper, we present a study of evolving artificial neural network controllers for autonomously playing maze-based video game. A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network(PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. …”
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Solution of optimal power flow using non-dominated sorting multi-objective based hybrid firefly and particle swarm optimization algorithm
Published 2020“…Simulation results were also compared with non-dominated sorting based multi-objective particle swarm optimization (MOPSO) and different optimization algorithms reported in the current literature. …”
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Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization
Published 2009“…The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal set of ANNs that could optimize two objectives in a single run; (1) maximize the mobile robot homing behavior whilst (2) minimize the hidden neurons involved in the feed-forward ANN. …”
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Pareto Ensembles for evolutionary Synthesis of Neurocontrollers in a 2D Maze-based video game
Published 2013“…In this paper, we present a study of evolving artificial neural network controllers for autonomously playing maze-based video game. A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network(PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. …”
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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Subjects:Conference Paper -
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah
Published 2022“…The results obtained are then analysed to assess the proposed solution’s performance in obtaining each deployment objective’s optimal value. Finally, the proposed algorithm’s effectiveness regarding node coverage, energy consumption, Pareto-optimal value, and algorithm execution time is validated using three Pareto-optimal metrics: including inverted generation distance (IGD), hypervolume, and diversity. …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks
Published 2022“…The results obtained are then analysed to assess the proposed solution's performance in obtaining each deployment objective's optimal value. Finally, the proposed algorithm's effectiveness regarding node coverage, energy consumption, Pareto-optimal value, and algorithm execution time is validated using three Pareto-optimal metrics: including inverted generation distance (IGD), hypervolume, and diversity. …”
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NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment
Published 2024“…From the research results, it can be seen that in genetic algorithms, resetting the population after reaching precocity can maintain the optimization characteristics of the population and have a high probability of obtaining Pareto solutions. …”
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Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…In an attempt to address this problem, the clustering-based method that utilizes crowding distance (CD) technique to balance the optimality of the objectives in Pareto optimal solution search is proposed. …”
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Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes
Published 2020“…A Pareto optimal set is a set of solutions that are non-dominated solutions frontier. …”
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Book Chapter -
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Non-dominated sorting Harris’s hawk multi-objective optimizer based on reference point approach
Published 2019“…The algorithm is able to improve the population diversity, convergence of non-dominated solutions toward the Pareto front, and prevent the population from trapping into local optimal. …”
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…The objective is to verify and compare the effectiveness of both algorithms in finding the optimal robot path in different types of global map environments. …”
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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources
Published 2025“…A smart memory-based strategy is incorporated into the algorithm to enhance solution optimality, convergence properties, and exploitation capabilities. …”
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A swarm intelligent approach for multi-objective optimization of compact heat exchangers
Published 2023Article
